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Proper orthogonal decomposition and its applications
Asia-Pacific Journal of Chemical Engineering, 2011AbstractThe proper orthogonal decomposition (POD) has become a very useful tool in the analysis and low‐dimensional modelling of flows. It provides an objective way of identifying the ‘coherent’ structures in a turbulent flow. The application of POD to the case of a thermally driven two‐dimensional flow of air in a horizontal rotating cylinder is ...
Sanjeev Sanghi, Nadeem Hasan
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Spatially compressed spectral proper orthogonal decomposition
Physical Review ERecovering coherent structures from sparse or partially sampled flow field data is inherently challenging, and traditional spectral proper orthogonal decomposition (SPOD) methods are further constrained by high computational cost, memory demands, and limited applicability.
Guanzhong Ma +4 more
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Proper orthogonal decomposition for pricing options
The Journal of Computational Finance, 2012In a paper that appeared in volume 2 (2011) of SIAM Financial Mathematics by R. Cont, N. Lantos and the author, it was shown that by writing the solution of the Black-Scholes partial dierential equation on a small set of basis functions the computing time can be dramatically reduced. In this study we show that it is in fact a P.O.D.
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Proper Orthogonal Decomposition in Option Pricing
2017In this chapter model order reduction (MOR) and the forward-backward duality are combined to generate forward and backward reduced models. We show that both resulting models are numerically efficient models and can in most situations reduce the computational effort in comparison with the full order models, when applying ADI and BDF2 time discretization
José P. Silva +3 more
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Probabilistic Proper Orthogonal Decomposition
2010Proper Orthogonal Decomposition (POD) is a method with much potential for identifying, locating and quantifying damage in structures [1-3]. POD can be interpreted as the maximum-likelihood solution to a probabilistic model called Probabilistic Principal Component Analysis (PPCA) [4].
HENSMAN J +3 more
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Proper orthogonal and dynamic mode decomposition of sunspot data
Philosophical Transactions Series A, Mathematical, Physical, and Engineering Sciences, 2021A B Albidah, W Brevis, V Fedun
exaly
Proper orthogonal decomposition & kriging strategies for design. [PDF]
, 2009 The proliferation of surrogate modelling techniques have facilitated the application of expensive, high fidelity simulations within design optimisation. Taking considerably fewer function evaluations than direct global optimisation techniques, such as genetic algorithms, surrogate models attempt to construct a surrogate of an objective function from an
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